Supply chain attacks are fast becoming the vector of choice for hackers. According to the Verizon 2022 Data Breach Investigations Report, 62% of system intrusion incidents came through an organization’s partner, often in the form of malicious code injected into a vendor’s software offerings.
Having up-to-date software is the first line of defense against such hacks. However, a recent IDC study found less than half of organizations (49.6%) are capable of rapidly deploying any form of patch or update.
One way federal agencies can keep their systems current is to use digital twins for security modeling. Let’s look at this practice and why it’s gaining popularity as the preferred way to patch mission-critical systems and maintain software integrity.
What are digital twins?
A digital twin is a digital copy of a physical object. Powered by a series of sensors and the application of artificial intelligence and machine learning, a digital twin can simulate any aspect of an object or process.
Consider an armored vehicle equipped with numerous sensors. Data collected by those sensors creates a digital representation or digital twin of the vehicle. The twin provides a real-time understanding of the vehicle’s health and status, including its location, engine performance, tire pressure and more. Digital twin technology can also be used to model scenarios and simulate conditions, down to an object’s subcomponents and how it relates to other systems and users.
Digital twin capabilities have many use cases, including aerospace and defense manufacturing, clinical research and smart city management. But the digital twin trend is also gaining momentum in IT security because of the speed, continuity of operations and peace of mind it brings to the patch management process.
Digital twins for security modeling
To ensure software integrity, traditional approaches to software updates and patches involve a great deal of custom coding, personalization and testing. According to IDC, 54% of organizations follow this process, despite the time and cost involved. The alternative is to patch in real time with no concern about the impact on systems, a method used by nearly 20% of organizations.
Neither approach is ideal. One drives a “don’t fail” approach and the other a “fail fast” approach. Digital twin technology can bridge this divide.
With a virtual digital twin simulating the impact of patches on system integrity and likely performance outcomes – in real time – federal IT pros can optimize the patch management process and quickly remediate vulnerabilities.
Prepare the infrastructure
As federal agencies consider adopting digital twins for security modeling, they need to assess whether they have the right tools and infrastructure to support this huge virtual production environment.
Because digital twins require a large amount of data to derive insights, IT pros should first consider the impact on the network and plan accordingly. With the proper monitoring strategy encompassing network, server, application and storage all working together, they can predict bottlenecks, improve capacity planning, and optimize performance.
Teams must also assess if they have the correct data analysis capabilities. As a starting point, they need to be able to easily correlate disparate data so they can synthesize and analyze data from multiple sensors on a shared common timeline. With these real-time insights, systems administrators can quickly predict performance issues before applying a patch, diagnose the root cause, and receive recommended corrective actions.
It’s well known the weakest link in the chain makes the whole system vulnerable. Agencies can’t take the chance there is an open door to supply chain attacks within their digital environment. By leveraging digital twin technologies for security modeling, federal IT pros can apply the “trust, but verify” model and stay current with all the updates, without the performance issues.
Brandon Shopp is group vice president of product at SolarWinds.